In machine learning, neural networks (e.g., a Recurrent Neural Networks (RNN) or Long Short-Term Memory (LSTM) networks) are employed to analyze text strings. The neural networks may predict a next character, word, or sentence in a text string in view of previously provided characters, words, or sentences. In certain cases, the neural networks classify elements of the text string (e.g., sentences, paragraphs, etc.) into one or more categories, such as whether the input element represents a positive or negative sentiment, or whether the input refers to history, philosophy, science, sports, etc.
While embodiments are described herein by way of example for several embodiments and illustrative drawings, those skilled in the art will recognize that the embodiments are not limited to the embodiments or drawings described. It should be understood that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include,” “including,” and “includes” mean including, but not limited to.